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13,017
datasets available to search
ShareScore release 0.9.0
Dataset results
13,017 results for “Positionning”
Mint-ChIP-seq from naive thymus-derived CD4-positive, alpha-beta T cell (ENCSR146KCI)
GEO Series GSE209005. Homo sapiens. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Microarray analysis of the effect of shRNA-mediated HAVCR2 knock-down (KD) in TIM-3-positive AML cell line, KASUMI-3
GEO Series GSE130328. Homo sapiens. 6 samples. Type: Expression profiling by array.
Expression profiling of Lgr5 positive adenoma cells.
GEO Series GSE37929. Mus musculus. 12 samples. Type: Expression profiling by array.
Hrp3 controls nucleosome positioning to suppress non-coding transcription in eu- and heterochromatin
GEO Series GSE40453. Schizosaccharomyces pombe. 10 samples. Type: Expression profiling by genome tiling array; Genome binding/occupancy profiling by high throughput sequencing.
Mint-ChIP-seq from naive thymus-derived CD8-positive, alpha-beta T cell (ENCSR923JIB)
GEO Series GSE177853. Homo sapiens. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Injury-Induced CLU-Positive Cardiomyocytes Drive Metabolic Reprogramming of Macrophage Function in Heart Regeneration [Spatial Transcriptomics]
GEO Series GSE254055. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
DNase-seq from CD4-positive, alpha-beta T cell (ENCSR824YLD)
GEO Series GSE170226. Homo sapiens. 1 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
The role of RUNX2 and BHLHE40 in pathologically relevant CD4-positive tissue-resident T-cells in Crohn's disease. (CITE-seq, CD4+ T cell) II
GEO Series GSE301689. Homo sapiens. 9 samples. Type: Expression profiling by high throughput sequencing; Other.
Hepatocyte identity and zonal position determine tumourigenic potential of mutant β-catenin
GEO Series GSE275864. Mus musculus. 48 samples. Type: Expression profiling by high throughput sequencing; Other.
PING 2.0: An R/Bioconductor package for nucleosome positioning using next-generation sequencing data
GEO Series GSE47073. Saccharomyces cerevisiae. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Custom scripts used in the study "Nucleosome positioning stability is a modulator of germline mutation rate variation across the human genome"
<p>Custom scripts and associated data used in the study "Nucleosome positioning stability is a modulator of germline mutation rate variation across the human genome"</p>
Face detection ensemble with methods using depth information to filter false positives
<p>%files (File.rar):<br> %ColorImageX.jpg is the color image<br> %SegImageX.jpg is the segmentation map <br> %SegImage2_X.jpg is the segmentation map obtained considering only Depth<br> %map</p> <p>%the .mat file<br> %DatasetFaceD{x}{1} depth map<br> %DatasetFaceD{x}{2} eyes coordinates<br> %DatasetFaceD{x}{3} calibration matrix, e.g used in face_dimension.m</p> <p> </p> <p>PS few images (7) used in the paper are no more available</p> <p> </p>
Figure 1 from: Li G, Lwin YH, Yang B, Qin T, Phothisath P, Maung K-W, Quan R-C, Li S (2020) Taxonomic revision and phylogenetic position of the flying squirrel genus Biswamoyopterus (Mammalia, Rodentia, Sciuridae, Pteromyini) on the northern Indo-China peninsula. ZooKeys 939: 65-85. https://doi.org/10.3897/zookeys.939.31764
Figure 1 Phylogeny of Pteromyini genera. Cited from Mercer and Roth (2003).
Carapa procero stomata positive and negative
<p>Dataset with positve and negative of stomata of the Carapa procero for training and validation. </p>
Cleaned and pre-processed MS/MS datset (build from all positive ionmode spectra in GNPS)
<p>MS/MS dataset build from data that was obtained from GNPS (accessed on 2020-05-11): <a href="https://gnps-external.ucsd.edu/gnpslibrary/ALL_GNPS.json">https://gnps-external.ucsd.edu/gnpslibrary/ALL_GNPS.json</a></p> <p>The data was cleaned and pre-processed using notebooks provided here: https://github.com/iomega/spec2vec_gnps_data_analysis/tree/master/notebooks</p> <ul> <li>112,956 spectra</li> <li>metadata was cleaned and corrected using matchms (https://github.com/matchms/matchms) and lookup routines using PubChem</li> <li>92,954 of the spectra have Smiles and InchiKey (13717 unique InchiKey in first 14 characters)</li> </ul>
Figure 8 from: Sorokina VS, Ovtshinnikova OG (2020) The position of the Azeliinae in the Muscidae (Diptera) based on musculature of the male terminalia. ZooKeys 975: 87-110. https://doi.org/10.3897/zookeys.975.55502
Figure 8 Male genitalia of Muscina stabulans (Fallén, 1817). Epandrial complex, inner view.
Figure 4 from: Sorokina VS, Ovtshinnikova OG (2020) The position of the Azeliinae in the Muscidae (Diptera) based on musculature of the male terminalia. ZooKeys 975: 87-110. https://doi.org/10.3897/zookeys.975.55502
Figure 4 Male genitalia of Drymeia firthiana (Huckett, 1965). Epandrial complex, inner view.
Differences in GPS variables according to playing formations and playing positions in U19 male soccer players
<p>The aims of this study were 1) to investigate Global Positioning System (GPS)-based match physical performance according to players’ playing position in three different playing formations (4-4-2, 3-5-2, 4-3-3) and 2) to analyse the differences in match performance between 1st and 2nd half. Twenty-three U19 elite male soccer players (age: 18 ± 1 year, height: 1.80 ± 0.04 m, body mass: 70.65 ± 6.02 kg), categorized as Central Back (CB, n = 5), Full Back (FB, n = 4), Central Midfielders (CM, n = 4), Wingers (W, n = 3), Strikers (S, n = 7), were monitored using 10 Hz GPS during 31 competitive matches. The results showed that FB and W always had the highest very high-speed running distance and number of sprints in all playing formations. Significant decrease in all GPS variables was observed in the 2nd half of the match for all playing positions. Strength coaches should adopt specific training regimes in accordance with players’ playing position.</p>
Figure 3 from: Naseka AM, Renaud CB (2020) Morphology-based taxonomic re-assessment of the Arctic lamprey, Lethenteron camtschaticum (Tilesius, 1811) and taxonomic position of other members of the genus. ZooKeys 991: 1-67. https://doi.org/10.3897/zookeys.991.54938
Figure 3 Syntype of Petromyzon kessleri, TGU 3 [no. 3699 in Ioganzen (1935b: table 3)], 182 mm TL.
Figure 4 from: Naseka AM, Renaud CB (2020) Morphology-based taxonomic re-assessment of the Arctic lamprey, Lethenteron camtschaticum (Tilesius, 1811) and taxonomic position of other members of the genus. ZooKeys 991: 1-67. https://doi.org/10.3897/zookeys.991.54938
Figure 4 Syntypes of Lampetra mitsukurii, ZMB 20638, 138.3 (a) and 140.1 (b) mm TL.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.